Continuous monitoring methods of cerebral compliance and compensatory reserve: a scoping review of human literature.

Objective.Continuous monitoring of cerebrospinal compliance (CC)/cerebrospinal compensatory reserve (CCR) is crucial for timely interventions and preventing more substantial deterioration in the context of acute neural injury, as it enables the early detection of abnormalities in intracranial pressure (ICP). However, to date, the literature on continuous CC/CCR monitoring is scattered and occasionally challenging to consolidate.Approach.We subsequently conducted a systematic scoping review of the human literature to highlight the available continuous CC/CCR monitoring methods.Main results.This systematic review incorporated a total number of 76 studies, covering diverse patient types and focusing on three primary continuous CC or CCR monitoring metrics and methods-Moving Pearson's correlation between ICP pulse amplitude waveform and ICP, referred to as RAP, the Spiegelberg Compliance Monitor, changes in cerebral blood flow velocity with respect to the alternation of ICP measured through transcranial doppler (TCD), changes in centroid metric, high frequency centroid (HFC) or higher harmonics centroid (HHC), and the P2/P1 ratio which are the distinct peaks of ICP pulse wave. The majority of the studies in this review encompassed RAP metric analysis (n= 43), followed by Spiegelberg Compliance Monitor (n= 11), TCD studies (n= 9), studies on the HFC/HHC (n= 5), and studies on the P2/P1 ratio studies (n= 6). These studies predominantly involved acute traumatic neural injury (i.e. Traumatic Brain Injury) patients and those with hydrocephalus. RAP is the most extensively studied of the five focused methods and exhibits diverse applications. However, most papers lack clarification on its clinical applicability, a circumstance that is similarly observed for the other methods.Significance.Future directions involve exploring RAP patterns and identifying characteristics and artifacts, investigating neuroimaging correlations with continuous CC/CCR and integrating machine learning, holding promise for simplifying CC/CCR determination. These approaches should aim to enhance the precision and accuracy of the metric, making it applicable in clinical practice.